Planning

The planning module turns a goal into a validated graph of steps and executes ready steps under explicit retry, timeout, approval, and persistence policies.

Planners and executors

Component	Implementations
Planner	static_planner, llm_planner
Executor	function_plan_executor, tool_plan_executor, agent_plan_executor, composite_plan_executor
Store	in_memory_plan_store, file_plan_store

llm_planner requests a JSON plan, repairs normalizable output, and validates tool and agent assignments. static_planner is useful for deterministic workflows and tests.

Minimal plan

namespace planning = wuwe::agent::planning;

auto planner = std::make_shared<planning::static_planner>(
  std::vector<planning::plan_step> {
    { .id = "inspect", .title = "Inspect input" },
    {
      .id = "summarize",
      .title = "Summarize result",
      .depends_on = { "inspect" },
    },
  });

auto executor = std::make_shared<planning::function_plan_executor>(
  [](const planning::plan_step& step,
     const planning::plan_execution_context&) {
    return planning::plan_step_result::completed(step.id + " completed");
  });

planning::plan_runner runner({
  .planner = planner,
  .executor = executor,
});

const auto result = runner.run({ .goal = "Inspect and summarize the input" });

Execution semantics

plan_runner validates the graph, finds dependency-ready steps, executes up to max_parallel_steps, records outputs and artifacts, and persists checkpoints when a store is configured.

plan_policy controls maximum steps and iterations, attempts per step, steps per run, parallelism, step and run timeouts, replanning, failure continuation, and resume behavior. resume() resets interrupted running steps by default and continues from persisted state.

Policy hooks can allow, deny, or require approval for each ready step. An approval provider supplies the host decision. A reflection gate can review completed steps before the run proceeds.

Validation and persistence

plan_validator checks identifiers, dependencies, cycles, limits, tool assignments, and agent assignments. plan_normalizer repairs safe structural issues. plan_codec serializes plans and results as JSON.

The file store is suitable for local checkpoints. Applications that need transactional shared storage can provide a custom plan_store backed by their database.

Planning events and trace callbacks expose plan creation, step transitions, approval requirements, revisions, cancellation, and completion.